A research team led by Shiori Hironaka, assistant professor of computer science and engineering projects at Toyohashi University of Technology, collected big data from social media in ten countries and analyzed the relationship between people’s connections and their behaviors on the internet. The researchers found that the users had the same characteristics in the tracking indices, which reflect the behavior of the users regardless of the country. Discovering common characteristics and differences in data that reflect social diversity can help people use data effectively according to their cultural differences, for example for marketing and effective information exchange.
The team collected data on the activity of more than 4,000,000 Twitter users in ten countries (Japan, USA, Brazil, UK, Philippines, Turkey, Indonesia, India, Mexico and Saudi Arabia) and statistically analyzed online relationships between connections and user behavior. This is the world’s first analysis of this type of data. The use of social media data for a variety of surveys and analysis is becoming more common as more people use social media. Data from the social media are understood as indirect observation of social situations; However, the nature of the data varies by country due to cultural differences and other factors, even if the data is observed similarly on social media. User behaviors are believed to reflect the cyberculture of the group to which the user belongs, so it is important to know the properties of social networks in order to be able to use them in different surveys.
The team analyzed the connections between users, focusing on the proximity of the areas in which they operate, since the purposes of using social networks can be closely related to the proximity of the areas of action of the users who are connected via social networks. To be specific, action areas tend to be close when using a social networking service to share with friends. When it comes to reading celebrity posts or news, the proximity of the action areas does not matter. Having examined the relationship between the nearness of action areas and user behavior in social networks, we compare the peculiarities of different countries.
As a result, we identified ten countries with common points regarding user characteristics related to the nearness of action areas. It is the index of what a user tracks towards his followers. If the follow ratio is high, a user is assumed to be accessed by people who want to read the user’s posts. We also found that users with longer profiles tend to be further removed from the areas of action of the connected users. However, the ten countries are not necessarily have this in common. Essentially, data about connections to social networks can express information about users around the world in the same way. However, this may not guarantee the expected accuracy for features such as friend recommendations and estimates of attributes such as the nature of the data individually differs due to cultural differences. The features identified are expected to help provide the best information to users from different countries and cultures.
